class_docstr: Class for the Free Water Elimination Diffusion Tensor Model 
docstr: Predict a signal for this TensorModel class instance given
  parameters.
  
  Parameters
  ----------
  fwdti_params : (..., 13) ndarray
      The last dimension should have 13 parameters: the 12 tensor
      parameters (3 eigenvalues, followed by the 3 corresponding
      eigenvectors) and the free water volume fraction.
  S0 : float or ndarray
      The non diffusion-weighted signal in every voxel, or across all
      voxels. Default: 1
  
  Returns
  -------
  S : (..., N) ndarray
      Simulated signal based on the free water DTI model
docstr_tok: ["Predict","a","signal","for","this","TensorModel","class","instance","given","parameters",".","Parameters","--","--","--","--","--","fwdti_params",":","(","...",",","13",")","ndarray","The","last","dimension","should","have","13","parameters",":","the","12","tensor","parameters","(","3","eigenvalues",",","followed","by","the","3","corresponding","eigenvectors",")","and","the","free","water","volume","fraction",".","S0",":","float","or","ndarray","The","non","diffusion-weighted","signal","in","every","voxel",",","or","across","all","voxels",".","Default",":","1","Returns","--","--","--","-","S",":","(","...",",","N",")","ndarray","Simulated","signal","based","on","the","free","water","DTI","model"]
code: def predict(self, fwdti_params, S0=1):
      """Predict a signal for this TensorModel class instance given
      parameters.
  
      Parameters
      ----------
      fwdti_params : (..., 13) ndarray
          The last dimension should have 13 parameters: the 12 tensor
          parameters (3 eigenvalues, followed by the 3 corresponding
          eigenvectors) and the free water volume fraction.
      S0 : float or ndarray
          The non diffusion-weighted signal in every voxel, or across all
          voxels. Default: 1
  
      Returns
      -------
      S : (..., N) ndarray
          Simulated signal based on the free water DTI model
      """
      return fwdti_prediction(fwdti_params, self.gtab, S0=S0)
  
imports: import warnings
  import numpy
  import scipy.optimize
  from dipy.reconst.base import ReconstModel
  from dipy.reconst.dti import TensorFit, design_matrix, decompose_tensor, _decompose_tensor_nan, from_lower_triangular, lower_triangular
  from dipy.reconst.dki import _positive_evals
  from dipy.reconst.vec_val_sum import vec_val_vect
  from dipy.core.ndindex import ndindex
  from dipy.core.gradients import check_multi_b
  from dipy.reconst.multi_voxel import multi_voxel_fit
label_desc: Use image node_id 3 for calling the FreeWaterTensorModel obj's underlying member method code with example usage: obj.predict(fwdti_params, S0) and returns: fwdti_prediction